License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.CP.2023.45
URN: urn:nbn:de:0030-drops-190825
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/19082/
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Golenvaux, Nicolas ; Gillard, Xavier ; Nijssen, Siegfried ; Schaus, Pierre

Partitioning a Map into Homogeneous Contiguous Regions: A Branch-And-Bound Approach Using Decision Diagrams (Short Paper)

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LIPIcs-CP-2023-45.pdf (0.7 MB)

Abstract

Regionalization is a crucial spatial analysis technique used for partitioning a map divided into zones into k continuous areas, optimizing the similarity of zone attributes within each area. This technique has a variety of applications in fields like urban planning, environmental management, and geographic information systems. The REDCAP algorithm is a well-known approach for addressing the regionalization problem. It consists of two main steps: first, it generates a spatially contiguous tree (SCT) representing the neighborhood structure of the set of spatial objects using a contiguity-constrained hierarchical clustering method. Second, it greedily removes k-1 edges from the SCT to create k regions. While this approach has proven to be effective, it may not always produce the most optimal solutions. We propose an alternative method for the second step, an exact dynamic programming (DP) formulation for the k-1 edges removal problem. This DP is solved using a multi-valued decision diagram (MDD)-based branch and bound solver leading to a more optimal solution. We compared our proposed method with the REDCAP state-of-the-art technique on real data and synthetic ones, using different instances of the regionalization problem and different supervised and unsupervised metrics. Our results indicate that our approach provides higher quality partitions than those produced by REDCAP at acceptable computational costs. This suggests that our method could be a viable alternative for addressing the regionalization problem in various applications.

BibTeX - Entry

@InProceedings{golenvaux_et_al:LIPIcs.CP.2023.45,
  author =	{Golenvaux, Nicolas and Gillard, Xavier and Nijssen, Siegfried and Schaus, Pierre},
  title =	{{Partitioning a Map into Homogeneous Contiguous Regions: A Branch-And-Bound Approach Using Decision Diagrams}},
  booktitle =	{29th International Conference on Principles and Practice of Constraint Programming (CP 2023)},
  pages =	{45:1--45:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-300-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{280},
  editor =	{Yap, Roland H. C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2023/19082},
  URN =		{urn:nbn:de:0030-drops-190825},
  doi =		{10.4230/LIPIcs.CP.2023.45},
  annote =	{Keywords: Regionalization, Redcap, Skater, Multivalued Decision Diagrams}
}

Keywords: Regionalization, Redcap, Skater, Multivalued Decision Diagrams
Collection: 29th International Conference on Principles and Practice of Constraint Programming (CP 2023)
Issue Date: 2023
Date of publication: 22.09.2023

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